Intranasal Orexin After Cardiac Arrest Leads to Increased Electroencephalographic Gamma Activity and Enhanced Neurologic Recovery in Rats.

OBJECTIVES: Prolonged cardiac arrest is known to cause global ischemic brain injury and functional impairment. Upon resuscitation, electroencephalographic recordings of brain activity begin to resume and can potentially be used to monitor neurologic recovery. We have previously shown that intrathecal orexin shows promise as a restorative drug and arousal agent in rodents. Our goal is to determine the electrophysiology effects of orexin in a rodent model of asphyxial cardiac arrest, focusing on the electroencephalographic activity in the gamma and super-gamma bands (indicative of return of higher brain function). DESIGN: Experimental animal study. SETTING: University-based animal research laboratory. SUBJECTS: Adult male Wistar rats. INTERVENTIONS: In an established model of asphyxial cardiac arrest (n = 24), we treated half of Wistar rats with orexin administered intranasally by atomizer 30 minutes post return of spontaneous circulation in one of two dose levels (10 and 50 µM); the rest were treated with saline as control. Continuous electroencephalographic recording was obtained and quantitatively analyzed for the gamma fraction. Gamma and high-frequency super-gamma band measures were compared against clinical recovery according to Neuro-Deficit Score. MEASUREMENTS AND MAIN RESULTS: Compared with the control cohort, the high-dose orexin cohort showed significantly better Neuro-Deficit Score 4 hours after return of spontaneous circulation (55.17 vs 47.58; p < 0.02) and significantly higher mean gamma fraction (0.251 vs 0.177; p < 0.02) in cerebral regions surveyed by rostral electrodes for the first 170 minutes after administration of orexin. CONCLUSIONS: Our findings support early and continuous monitoring of electroencephalography-based gamma activity as a marker of better functional recovery after intranasal administration of orexin as measured by Neuro-Deficit Score in an established animal model of asphyxial cardiac arrest.

Band specific changes in thalamocortical synchrony in field potentials after cardiac arrest induced global hypoxia.

Cardiac Arrest (CA) leads to a global hypoxic-ischemic injury in the brain leading to a poor neurological outcome. Understanding the mechanisms of functional disruption in various regions of the brain may be essential for the development of improved diagnostic and therapeutic solutions. Using controlled laboratory experiment with animal models of CA, our primary focus here is on understanding the functional changes in the thalamus and the cortex, associated with the injury and acute recovery upon resuscitation. Specifically, to study the changes in thalamocortical synchrony through these periods, we acquired local field potentials (LFPs) from the ventroposterior lateral (VPL) nucleus of the thalamus and the forelimb somatosensory cortex (S1FL) in rats after asphyxial CA. Band-specific relative Hilbert phases were used to analyze synchrony between the LFPs. We observed that the CA induced global ischemia changes the local phase-relationships by introducing a phase-lag in both the thalamus and the cortex, while the synchrony between the two regions is nearly completely lost after CA.

Optimal control-based bayesian detection of clinical and behavioral state transitions.

Accurately detecting hidden clinical or behavioral states from sequential measurements is an emerging topic in neuroscience and medicine, which may dramatically impact neural prosthetics, brain-computer interface and drug delivery. For example, early detection of an epileptic seizure from sequential electroencephalographic (EEG) measurements would allow timely administration of anticonvulsant drugs or neurostimulation, thus reducing physical impairment and risks of overtreatment. We develop a Bayesian paradigm for state transition detection that combines optimal control and Markov processes. We define a hidden Markov model of the state evolution and develop a detection policy that minimizes a loss function of both probability of false positives and accuracy (i.e., lag between estimated and actual transition time). Our strategy automatically adapts to each newly acquired measurement based on the state evolution model and the relative loss for false positives and accuracy, thus resulting in a time varying threshold policy. The paradigm was used in two applications: 1) detection of movement onset (behavioral state) from subthalamic single unit recordings in Parkinson's disease patients performing a motor task; 2) early detection of an approaching seizure (clinical state) from multichannel intracranial EEG recordings in rodents treated with pentylenetetrazol chemoconvulsant. Our paradigm performs significantly better than chance and improves over widely used detection algorithms.

A Bayesian framework for analyzing iEEG data from a rat model of epilepsy.

The early detection of epileptic seizures requires computing relevant statistics from multivariate data and defining a robust decision strategy as a function of these statistics that accurately detects the transition from the normal to the peri-ictal (problematic) state. We model the afflicted brain as a hidden Markov model (HMM) with two hidden clinical states (normal and peri-ictal). The output of the HMM is a statistic computed from multivariate neural measurements. A Bayesian framework is developed to analyze the a posteriori conditional probability of being in peri-ictal state given current and past output measurements. We apply this method to multichannel intracortical EEGs (iEEGs) from the thalamo-cortical ictal pathway in an epilepsy rat model. We first define the output statistic as the max singular value of a connectivity matrix computed on the EEG channels with spectral techniques Then, we estimate the HMM transition probabilities from this statistic and track the a posteriori probability of being in peri-ictal state (the "information state variable"). We show how the information state variable changes as a function of time and we predict a seizure when this variable becomes greater than 0.5. This Bayesian strategy significantly improves over chance level and heuristically-chosen threshold-based predictors.

Target-specific catecholamine elevation induced by anticonvulsant thalamic deep brain stimulation.

PURPOSE: Anterior thalamic nucleus (AN) deep brain stimulation (DBS) is effective in raising EEG and clonic seizure threshold in experimental models. Little is known about the specific properties of DBS that afford its anticonvulsant effect. We sought to test the hypothesis that experimental seizures and the anticonvulsant action of AN DBS alter the underlying regional neurochemistry of AN, specifically with facilitation of the serotonergic system to local electrical stimulation. METHODS: Halothane-anesthetized adult Sprague-Dawley male rats underwent stereotactically guided bilateral placement of bipolar stimulating steel electrodes and dialysis probes-guide cannulae in AN and posterior thalamus (PT), and placement of four epidural EEG screw electrodes 48 h before experiments. Both stimulated (AN DBS) and nonstimulated (NO DBS) animals (n=7 per group) were infused with i.v. pentylenetetrazol (PTZ, 5.5 mg/kg/min). Simultaneous thalamic and cortical EEG were recorded, and microdialysis samples were collected from AN and PT in 20-min epochs. AN stimulation was delivered (150 microA; 0.1-ms pulse duration) 40 min before and continued during PTZ infusion. RESULTS: Bilateral AN stimulation delayed the onset of EEG seizures compared with controls: 82+/-8 vs. 58+/-5 min (p=0.02). PTZ infusion alone, or together with stimulation, resulted in a steady increase in norepinephrine (NE), but not dopamine, at AN and PT sites (p<0.001). Although extracellular serotonin was measured at very low levels, the metabolite, 5-hydroxyindoleacetic acid (5-HIAA) increased selectively in AN after stimulation and during preconvulsant infusion of PTZ (p<0.001), returning to baseline after the first generalized seizure. CONCLUSIONS: These data suggest that PTZ and DBS together enhance the nonselective release of NE in thalamic nuclei while specifically stimulating AN-localized serotonin. Low serotonin levels at baseline and during STIM alone or PTZ infusion may indicate efficient reuptake systems for serotonin, with 5-HIAA serving as a surrogate marker for serotonergic activity. Modulation of the AN-specific serotonergic activity may be critical in altering PTZ seizure threshold and be an important neurotransmitter system underlying the efficacy of AN DBS.

Sinusoidal modeling of ictal activity along a thalamus-to-cortex seizure pathway I: new coherence approaches.

Understanding associations in neuronal circuitry is critical for tracing epilepsy pathways. Two new methods of measuring coherence between field potentials and EEG channels are proposed for modeling the level of linear association between channels during epileptic seizures. These methods rely upon modeling the repetitive clonic seizure activity as a sum of sinusoids with varying degrees of phase locking. Estimating the amplitude of sinusoids from correlation and cross-correlation time domain data, we can find the coherences from a ratio of these amplitudes. One method utilizes amplitude finding from the multiple signal classification (MUSIC) technique. The other method uses alterations in amplitude of individual sinusoids and their ratios in a matrix pencil equation formed from cross- and auto-correlation matrices. The corresponding generalized eigenvalues of these equations form the coherence ratios. This utilizes the estimation of signal parameters using rotational invariance techniques (ESPRIT) algorithm to arrive at coherence amplitude ratios. Simulations illustrate that the MUSIC method provides better noise immunity as it out-performs the conventional Fourier transform-based method for coherence estimation. Both coherence estimators reflect presence of sinusoidal components that are propagated or not propagated along a particular transmission pathway. We illustrate the value of both methods by examining the strength of correlation between seizure EEG from specific thalamic nuclei and cortex in a rodent model of generalized epilepsy. The pentylenetetrazol (PTZ) chemoconvulsant model in rats reflects selective activation of the anterior thalamic nucleus. Using both methods, this neuronal element has much larger coherence with cortex than another thalamic region, the posterior thalamus (p < 0.05). These methods isolate the unique contribution of anterior thalamus in the formation of an ictal network and corroborate earlier conventional or periodogram techniques.

Electric field and stimulating influence generated by deep brain stimulation of the subthalamic nucleus.

OBJECTIVE: The goal of this project was to develop a quantitative understanding of the volume of axonal tissue directly activated by deep brain stimulation (DBS) of the subthalamic nucleus (STN). METHODS: The 3-dimensionally inhomogeneous and anisotropic tissue medium surrounding DBS electrodes complicates our understanding of the electric field and tissue response generated by the stimulation. We developed finite element computer models to address the effects of DBS in a homogeneous isotropic medium, and a medium with tissue conductivity properties derived from human diffusion tensor magnetic resonance data. The second difference of the potential distribution generated in the tissue medium was used as a predictor of the volume of tissue supra-threshold for axonal activation. RESULTS: The model predicts that clinically effective stimulation parameters (-3 V; 0.1 ms; 150 Hz) result in activation of large diameter (5.7 microm) myelinated axons over a volume that spreads outside the borders of the STN. The shape of the activation volume was dependent on the strong dorsal-ventral anisotropy of the internal capsule, and the moderate anterior-posterior anisotropy of the region around zona incerta. CONCLUSIONS: Small deviations ( approximately 1 mm) in the electrode position within STN can substantially alter the shape of the activation volume as well as its spread to neighboring structures. SIGNIFICANCE: STN DBS represents an effective treatment for medically refractory movement disorders such as Parkinson's disease. However, stimulation induced side effects such as tetanic muscle contraction, speech disturbance and ocular deviation are not uncommon. Quantitative characterization of the spread of stimulation will aid in the development of techniques to maximize the efficacy of DBS.

Cellular effects of deep brain stimulation: model-based analysis of activation and inhibition.

Deep brain stimulation (DBS) is an effective therapy for medically refractory movement disorders. However, fundamental questions remain about the effects of DBS on neurons surrounding the electrode. Experimental studies have produced apparently contradictory results showing suppression of activity in the stimulated nucleus, but increased inputs to projection nuclei. We hypothesized that cell body firing does not accurately reflect the efferent output of neurons stimulated with high-frequency extracellular pulses, and that this decoupling of somatic and axonal activity explains the paradoxical experimental results. We studied stimulation using the combination of a finite-element model of the clinical DBS electrode and a multicompartment cable model of a thalamocortical (TC) relay neuron. Both the electric potentials generated by the electrode and a distribution of excitatory and inhibitory trans-synaptic inputs induced by stimulation of presynaptic terminals were applied to the TC relay neuron. The response of the neuron to DBS was primarily dependent on the position and orientation of the axon with respect to the electrode and the stimulation parameters. Stimulation subthreshold for direct activation of TC relay neurons caused suppression of intrinsic firing (tonic or burst) activity during the stimulus train mediated by activation of presynaptic terminals. Suprathreshold stimulation caused suppression of intrinsic firing in the soma, but generated efferent output at the stimulus frequency in the axon. This independence of firing in the cell body and axon resolves the apparently contradictory experimental results on the effects of DBS. In turn, the results of this study support the hypothesis of stimulation-induced modulation of pathological network activity as a therapeutic mechanism of DBS.

Prediction of PTZ-induced seizures using wavelet-based residual entropy of cortical and subcortical field potentials.

Our proposed algorithm for seizure prediction is based on the principle that seizure build-up is always preceded by constantly changing bursting levels. We use a novel measure of residual subband wavelet entropy (RSWE) to directly estimate the entropy of bursts, which is otherwise obscured by the ongoing background activity. Our results are obtained using a slow infusion anesthetized pentylenetetrazol (PTZ) rat model in which we record field potentials (FPs) from frontal cortex and two thalamic areas (anterior and posterior nuclei). In each frequency band, except for the theta-delta frequency bands, we observed a significant build-up of RSWE from the preictal period to the first ictal event (p < or = 0.05) in cortex. Significant differences were observed between cortical and thalamic RSWE (p < or = 0.05) subsequent to seizure development. A key observation is the twofold increase in mean cortical RSWE from the preictal to interictal period. Exploiting this increase, we develop a slope change detector to discern early acceleration of entropy and predict the approaching seizure. We use multiple observations through sequential detection of slope changes to enhance the sensitivity of our prediction. Using the proposed method applied to a cohort of four rats subjected to PTZ infusion, we were able to predict the first seizure episode 28 min prior to its occurrence.

Anterior thalamic mediation of experimental seizures: selective EEG spectral coherence.

PURPOSE: Physiological evidence has shown that the anterior thalamus (AN) and its associated efferents/afferents constitute an important propagation pathway for pentylenetetrazol (PTZ)-mediated generalized seizures in rodents. Previous work demonstrated metabolic, physical, chemical, and electrical stimulation data supporting a role for AN in the expression of PTZ seizures. We now extend these observations through examination of neuroelectric signal indicators during seizure epochs. We show that the EEG recorded from AN is highly coherent with surface cortical (CTX) EEG during the immediate preconvulsant period and during the ictal stateough. METHODS: Awake rats were continuously infused with PTZ until clonic seizures were recorded by using both subcortical AN, posterior thalamus (PT), or hippocampal (HPC) bipolar electrodes and cortical EEG. Through the signal-analysis techniques of ordinary and partial coherence, it was possible to focus selectively on signal correlations between AN and CTX (AN/CTX) by removing the effects of unaffiliated regions such as PT and HPC. RESULTS: Coherence of PT/CTX was observed to be modest, and partial coherence of PT/CTX with the effects of AN/CTX removed did not improve the signal coherence of PT/CTX (PT/CTX-AN). In contrast, AN/CTX coherence was observed to be high, with undiminished correlation when PT/CTX influence was removed (AN/CTX-PT). The most robust band of AN/CTX coherence was centered around the spike-wave clonic frequency of 1-3 Hz. Partial multiple coherence-analysis techniques were used to remove the possible signal contributions from hippocampus in addition to PT. The AN/CTX coherence remained fully preserved in the low-frequency bands. CONCLUSIONS: These data provide electrophysiologic evidence supporting the special role of the anterior thalamus in the propagation of seizure activity between subcortex and cortex.

Neurological recovery by EEG bursting after resuscitation from cardiac arrest in rats.

INTRODUCTION: The return of neurological function during the early period after resuscitation from cardiac arrest (CA) has not been evaluated systematically. We report the temporal analysis of EEG bursting pattern during the very early periods after resuscitation. DESIGN/METHOD: A balanced group of good and poor outcome animals was selected from a population of rats subjected to either 5 or 7 min of asphyxial cardiac arrest (ACA) on the basis of a single criteria: 24 h neurobehavioral function based on the neurodeficit score (NDS). The EEGs of six consecutive good outcome rats (NDS > or = 60) and six consecutive poor outcome rats (NDS < 60) were selected for the study. The EEGs of these animals were given to two EEG examiners who were blinded to the selection process, the experimental conditions and the neurobehavioral recovery. The EEG bursting characteristics, such as rate, peak and duration of bursting were studied. RESULTS: There was significantly higher EEG bursting in the good outcome animals (P < 0.05) and the burst complexes evolved into continuous activity by 90 min. Lower frequency bursting that persisted and failed to evolve into continuous activity was observed in the poor outcome group. CONCLUSION: Increased EEG bursting during first 30-40 min after resuscitation from moderate to severe ACA was observed in rats with good neurological outcome at 24 h. Early EEG bursting patterns may provide additional prognostication after resuscitation from CA.